Evaluation of biofilm image thresholding methods

Tools of the Trade: Image Analysis Programs for Confocal Laser-Scanning Microscopy Studies of Biofilms and Considerations for Their Use by Experimental Researchers

Confocal laser-scanning microscopy (CLSM) is the bedrock of the microscopic visualization of biofilms. Previous applications of CLSM in biofilm studies have largely focused on observations of bacterial or fungal elements of biofilms, often seen as aggregates or mats of cells. However, the field of biofilm research is moving beyond qualitative observations alone, toward the quantitative analysis of the structural and functional features of biofilms, across clinical, environmental, and laboratory conditions. In recent times, several image analysis programs have been developed to extract and quantify biofilm properties from confocal micrographs. These tools not only vary in their scope and relevance to the specific biofilm features under study but also with respect to the user interface, compatibility with operating systems, and raw image requirements. Understanding these considerations is important when selecting tools for quantitative biofilm analysis, including at the initial experimental stages of image acquisition. In this review, we provide an overview of image analysis programs for confocal micrographs of biofilms, with a focus on tool selection and image acquisition parameters that are relevant for experimental researchers to ensure reliability and compatibility with downstream image processing.

Application of filter media surface hydrophobic modification to reduce bioclogging in the infiltration system

Bioclogging is a commonly encountered operational issue that lowers hydraulic conductivity and the overall performance of the infiltration systems. In this paper, a novel processing for alleviating bioclogging by filter media surface hydrophobic modification was presented. Two-dimensional porous media cells were used to observe the influence of hydrophobic modification on biofilm growth in the pore structure. Moreover, two continuous-flow columns packed with gravel, one of which half gravel was hydrophobically modified, were operated with artificial wastewater to verify the effect of hydrophobic modification on bioclogging alleviation. The results showed that the biofilm growth in the cell with hydrophobic modification was slow, and the biomass was less and liable to wipe off after hydrophobic treatment. Meanwhile, the hydraulic efficiency of the flow seepage field was also improved after hydrophobic treatment. The column tests results showed that the hydraulic conductivity of the filter bed with hydrophobic modification (Column B) decreased more slowly than that of another without hydrophobic modification (Column A). Column B had the hydraulic conductivity (k) of 0.66 cm/s in the final stage of the experiment, while the k of Column A was 0.14 cm/s. It verified that hydrophobic modification of partial filter media can alleviate the bioclogging problem of the infiltration systems to some extent. The results provide a new idea and potential technical support for solving bioclogging problem.

Bioclogging alleviation for constructed wetland based on the interaction among biofilm growth and hydrodynamics

Bioclogging is the most crucial operation problem of the constructed wetlands, which reduce its removal efficiency and life span. A strategy through properly increasing hydraulic loading is proposed in this study to alleviate the bioclogging for CWs. The two-dimensional porous media flow cell (2D PMFC) test indicated that a quadratic correlation was found between local biofilms growth rate and the near-wall Reynolds number (r > 0.765, p < 0.05). The biofilm growth rate declined with the flowrate when Re exceeded about 6.0. It was also found that the higher flowrate (6 mL/min) lead to the homogeneous biofilm and velocity distribution in the PMFC. The column test indicated that the highest hydraulic loading (9.2 cm/h) produced the smallest decrease in hydraulic conductivity, which was 80 times more than that of low hydraulic load (3.0 cm/h) at the end (40 days) of experiment. Moreover, the relatively homogenized distribution of biofilm was found along the column with the highest hydraulic loading, which confirmed that the proper increase in hydraulic loading can alleviate bioclogging.

Quantifying biofilm propagation on chemically modified surfaces

Conditions affecting biofilm formation differ among bacterial species and this presents a challenge to studying biofilms in the lab. This work leverages functionalized silanes to control surface chemistry in the study of early biofilm propagation, quantified with a semi-automated image processing algorithm. These methods support the study of Pantoea sp. YR343, a gram-negative bacterium isolated from the poplar rhizosphere. We found that Pantoea sp. YR343 does not readily attach to hydrophilic surfaces but will form biofilms with a “honeycomb” morphology on hydrophobic surfaces. Our image processing algorithm described here quantified the evolution of the honeycomb morphology over time, and found the propagation to display a logarithmic behavior. This methodology was repeated with a flagella-deficient fliR mutant of Pantoea sp. YR343 which resulted in reduced surface attachment. Quantifiable differences between Pantoea WT and ΔfliR biofilm morphologies were captured by the image processing algorithm, further demonstrating the insight gained from these methods.

Advances and opportunities in image analysis of bacterial cells and communities

The cellular morphology and sub-cellular spatial structure critically influence the function of microbial cells. Similarly, the spatial arrangement of genotypes and phenotypes in microbial communities has important consequences for cooperation, competition, and community functions. Fluorescence microscopy techniques are widely used to measure spatial structure inside living cells and communities, which often results in large numbers of images that are difficult or impossible to analyze manually. The rapidly evolving progress in computational image analysis has recently enabled the quantification of a large number of properties of single cells and communities, based on traditional analysis techniques and convolutional neural networks. Here, we provide a brief introduction to core concepts of automated image processing, recent software tools and how to validate image analysis results. We also discuss recent advances in image analysis of microbial cells and communities, and how these advances open up opportunities for quantitative studies of spatiotemporal processes in microbiology, based on image cytometry and adaptive microscope control.

Quantitative image analysis of microbial communities with BiofilmQ

Biofilms are microbial communities that represent a highly abundant form of microbial life on Earth. Inside biofilms, phenotypic and genotypic variations occur in three-dimensional space and time; microscopy and quantitative image analysis are therefore crucial for elucidating their functions. Here, we present BiofilmQ—a comprehensive image cytometry software tool for the automated and high-throughput quantification, analysis and visualization of numerous biofilm-internal and whole-biofilm properties in three-dimensional space and time.

BiofilmQ is an image cytometry software tool that enables the visualization, quantification and analysis of biofilm properties, providing insights into their structure and function.

Influence of High Intensity Focused Ultrasound on the Microstructure and c-di-GMP Signaling of Pseudomonas aeruginosa Biofilms

Bacterial biofilms are typically more tolerant to antimicrobials compared to bacteria in the planktonic phase and therefore require alternative treatment approaches. Mechanical biofilm disruption from ultrasound may be such an alternative by circumventing rapid biofilm adaptation to antimicrobial agents. Although ultrasound facilitates biofilm dispersal and may enhance the effectiveness of antimicrobial agents, the resulting biological response of bacteria within the biofilms remains poorly understood. To address this question, we investigated the microstructural effects of Pseudomonas aeruginosa biofilms exposed to high intensity focused ultrasound (HIFU) at different acoustic pressures and the subsequent biological response. Confocal microscopy images indicated a clear microstructural response at peak negative pressures equal to or greater than 3.5 MPa. In this pressure amplitude range, HIFU partially reduced the biomass of cells and eroded exopolysaccharides from the biofilm. These pressures also elicited a biological response; we observed an increase in a biomarker for biofilm development (cyclic-di-GMP) proportional to ultrasound induced biofilm removal. Cyclic-di-GMP overproducing mutant strains were also more resilient to disruption from HIFU at these pressures. The biological response was further evidenced by an increase in the relative abundance of cyclic-di-GMP overproducing variants present in the biofilm after exposure to HIFU. Our results, therefore, suggest that both physical and biological effects of ultrasound on bacterial biofilms must be considered in future studies.

A Multiscale CNN-CRF Framework for Environmental Microorganism Image Segmentation

To assist researchers to identify Environmental Microorganisms (EMs) effectively, a Multiscale CNN-CRF (MSCC) framework for the EM image segmentation is proposed in this paper. There are two parts in this framework: The first is a novel pixel-level segmentation approach, using a newly introduced Convolutional Neural Network (CNN), namely, “mU-Net-B3”, with a dense Conditional Random Field (CRF) postprocessing. The second is a VGG-16 based patch-level segmentation method with a novel “buffer” strategy, which further improves the segmentation quality of the details of the EMs. In the experiment, compared with the state-of-the-art methods on 420 EM images, the proposed MSCC method reduces the memory requirement from 355 MB to 103 MB, improves the overall evaluation indexes (Dice, Jaccard, Recall, Accuracy) from 85.24%, 77.42%, 82.27%, and 96.76% to 87.13%, 79.74%, 87.12%, and 96.91%, respectively, and reduces the volume overlap error from 22.58% to 20.26%. Therefore, the MSCC method shows great potential in the EM segmentation field.

Eradication of Candida albicans persister cell biofilm by the membranotropic peptide gH625

Biofilm formation poses an important clinical trouble due to resistance to antimicrobial agents; therefore, there is an urgent demand for new antibiofilm strategies that focus on the use of alternative compounds also in combination with conventional drugs. Drug-tolerant persisters are present in Candida albicans biofilms and are detected following treatment with high doses of amphotericin B. In this study, persisters were found in biofilms treated with amphotericin B of two clinical isolate strains, and were capable to form a new biofilm in situ. We investigated the possibility of eradicating persister-derived biofilms from these two Candida albicans strains, using the peptide gH625 analogue (gH625-M). Confocal microscopy studies allowed us to characterize the persister-derived biofilm and understand the mechanism of interaction of gH625-M with the biofilm. These findings confirm that persisters may be responsible for Candida biofilm survival, and prove that gH625-M was very effective in eradicating persister-derived biofilms both alone and in combination with conventional antifungals, mainly strengthening the antibiofilm activity of fluconazole and 5-flucytosine. Our strategy advances our insights into the development of effective antibiofilm therapeutic approaches.

A Comparison of Thresholding Methods for Forensic Reconstruction Studies Using Fluorescent Powder Proxies for Trace Materials

Image segmentation is a fundamental precursor to quantitative image analysis. At present, no standardised methodology exists for segmenting images of fluorescent proxies for trace evidence. Experiments evaluated (i) whether manual segmentation is reproducible within and between examiners (with three participants repeatedly tracing three images) (ii) whether manually defining a threshold level offers accurate and reproducible results (with 20 examiners segmenting 10 images), and (iii) whether a global thresholding algorithm might perform with similar accuracy, while offering improved reproducibility and efficiency (16 algorithms tested). Statistically significant differences were seen between examiners’ traced outputs. Manually thresholding produced good accuracy on average (within ±1% of the expected values), but poor reproducibility (with multiple outliers). Three algorithms (Yen, MaxEntropy, and RenyiEntropy) offered similar accuracy, with improved reproducibility and efficiency. Together, these findings suggest that appropriate algorithms could perform thresholding tasks as part of a robust workflow for reconstruction studies employing fluorescent proxies for trace evidence.

A Sensitive Thresholding Method for Confocal Laser Scanning Microscope Image Stacks of Microbial Biofilms

Biofilms are surface-attached microbial communities whose architecture can be captured with confocal microscopy. Manual or automatic thresholding of acquired images is often needed to help distinguish biofilm biomass from background noise. However, manual thresholding is subjective and current automatic thresholding methods can lead to loss of meaningful data. Here, we describe an automatic thresholding method designed for confocal fluorescent signal, termed the biovolume elasticity method (BEM). We evaluated BEM using confocal image stacks of oral biofilms grown in pooled human saliva. Image stacks were thresholded manually and automatically with three different methods; Otsu, iterative selection (IS), and BEM. Effects on biovolume, surface area, and number of objects detected indicated that the BEM was the least aggressive at removing signal, and provided the greatest visual and quantitative acuity of single cells. Thus, thresholding with BEM offers a sensitive, automatic, and tunable method to maintain biofilm architectural properties for subsequent analysis.

Morphological analysis of pore size and connectivity in a thick mixed-culture biofilm

Morphological parameters are commonly used to predict transport and metabolic kinetics in biofilms. Yet, quantification of biofilm morphology remains challenging because of imaging technology limitations and lack of robust analytical approaches. We present a novel set of imaging and image analysis techniques to estimate internal porosity, pore size distributions, and pore network connectivity to a depth of 1 mm at a resolution of 10 µm in a biofilm exhibiting both heterotrophic and nitrifying activities. Optical coherence tomography (OCT) scans revealed an extensive pore network with diameters as large as 110 µm directly connected to the biofilm surface and surrounding fluid. Thin-section fluorescence in situ hybridization microscopy revealed that ammonia-oxidizing bacteria (AOB) distributed through the entire thickness of the biofilm. AOB were particularly concentrated in the biofilm around internal pores. Areal porosity values estimated from OCT scans were consistently lower than those estimated from multiphoton laser scanning microscopy, though the two imaging modalities showed a statistically significant correlation (r = 0.49, p < 0.0001). Estimates of areal porosity were moderately sensitive to gray-level threshold selection, though several automated thresholding algorithms yielded similar values to those obtained by manually thresholding performed by a panel of environmental engineering researchers (±25% relative error). These findings advance our ability to quantitatively describe the geometry of biofilm internal pore networks at length scales relevant to engineered biofilm reactors and suggest that internal pore structures provide crucial habitat for nitrifier growth.

Understanding the fundamental mechanisms of biofilms development and dispersal: BIAM (Biofilm Intensity and Architecture Measurement), a new tool for studying biofilms as a function of their architecture and fluorescence intensity

Confocal laser scanning microscopy (CLSM) is one of the most relevant technologies for studying biofilms in situ. Several tools have been developed to investigate and quantify the architecture of biofilms. However, an approach to quantify correctly the evolution of intensity of a fluorescent signal as a function of the structural parameters of a biofilm is still lacking. Here we present a tool developed in the ImageJ open source software that can be used to extract both structural and fluorescence intensity from CLSM data: BIAM (Biofilm Intensity and Architecture Measurement). This is of utmost significance when studying the fundamental mechanisms of biofilm growth, differentiation and development or when aiming to understand the effect of external molecules on biofilm phenotypes. In order to provide an example of the potential of such a tool in this study we focused on biofilm dispersion. cis-2-Decenoic acid (CDA) is a molecule known to induce biofilm dispersion of multiple bacterial species. The mechanisms by which CDA induces dispersion are still poorly understood. To investigate the effects of CDA on biofilms, we used a reporter strain of Escherichia coli (E. coli) that expresses the GFPmut2 protein under control of the rrnBP1 promoter. Experiments were done in flow cells and image acquisition was made with CLSM. Analysis carried out using the new tool, BIAM, indicates that CDA affects the fluorescence intensity of the biofilm structures as well as biofilm architectures. Indeed, our results demonstrate that CDA removes more than 35% of biofilm biovolume and suggest that it results in an increase of the biofilm's mean fluorescence intensity (MFI) by more than 26% compared to the control biofilm in the absence of CDA.

A method for rapid quantitative assessment of biofilms with biomolecular staining and image analysis

The accumulation of bacteria in surface-attached biofilms can be detrimental to human health, dental hygiene, and many industrial processes. Natural biofilms are soft and often transparent, and they have heterogeneous biological composition and structure over micro- and macroscales. As a result, it is challenging to quantify the spatial distribution and overall intensity of biofilms. In this work, a new method was developed to enhance the visibility and quantification of bacterial biofilms. First, broad-spectrum biomolecular staining was used to enhance the visibility of the cells, nucleic acids, and proteins that make up biofilms. Then, an image analysis algorithm was developed to objectively and quantitatively measure biofilm accumulation from digital photographs and results were compared to independent measurements of cell density. This new method was used to quantify the growth intensity of Pseudomonas putida biofilms as they grew over time. This method is simple and fast, and can quantify biofilm growth over a large area with approximately the same precision as the more laborious cell counting method. Stained and processed images facilitate assessment of spatial heterogeneity of a biofilm across a surface. This new approach to biofilm analysis could be applied in studies of natural, industrial, and environmental biofilms.

Graphical abstract

Assessing the influence of biofilm surface roughness on mass transfer by combining optical coherence tomography and two-dimensional modeling

Imaging and modeling are two major approaches in biofilm research to understand the physical and biochemical processes involved in biofilm development. However, they are often used separately. In this study we combined these two approaches to investigate substrate mass transfer and mass flux. Cross-sectional biofilm images were acquired by means of optical coherence tomography (OCT) for biofilms grown on carriers. A 2D biofilm model was developed incorporating OCT images as well as a simplified biofilm geometry serving as structural templates. The model incorporated fluid flow, substrate transfer and biochemical conversion of substrates and simulated the hydrodynamics surrounding the biofilm structure as well as the substrate distribution. The method allowed detailed analysis of the hydrodynamics and mass transfer characteristics at the micro-scale. Biofilm activity with respect to substrate fluxes was compared among different combinations of flow, substrate availability and biomass density. The combined approach revealed that higher substrate fluxes at heterogeneous biofilm surface under two conditions: pure diffusion and when high flow velocity along the biofilms surface renders the whole liquid-biofilm interface to be highly active. In-between the two conditions the substrate fluxes across the surface of smooth biofilm geometry were higher than that of the heterogeneous biofilms.

Electrochemical scaffold generates localized, low concentration of hydrogen peroxide that inhibits bacterial pathogens and biofilms

We hypothesized that low concentrations of H2O2 could be generated through the electrochemical conversion of oxygen by applying an electric potential to a conductive scaffold and produce a low, but constant, concentration of H2O2 that would be sufficient to destroy biofilms. To test our hypothesis we used a multidrug-resistant Acinetobacter baumannii strain, because this species is often implicated in difficult-to-treat biofilm infections. We used conductive carbon fabric as the scaffold material ("e-scaffold"). In vitro experiments demonstrated the production of a maximum constant concentration of ~25 μM H2O2 near the e-scaffold surface. An e-scaffold was overlaid onto an existing A. baumannii biofilm, and within 24 h there was a ~4-log reduction in viable bacteria with an ~80% decrease in biofilm surface coverage. A similar procedure was used to overlay an e-scaffold onto an existing A. baumannii biofilm that was grown on a porcine explant. After 24 h, there was a ~3-log reduction in viable bacteria from the infected porcine explants with no observable damage to the underlying mammalian tissue based on a viability assay and histology. This research establishes a novel foundation for an alternative antibiotic-free wound dressing to eliminate biofilms.

Vancomycin and maltodextrin affect structure and activity of Staphylococcus aureus biofilms

Hyperosmotic agents such as maltodextrin negatively impact bacterial growth through osmotic stress without contributing to drug resistance. We hypothesized that a combination of maltodextrin (osmotic agent) and vancomycin (antibiotic) would be more effective against Staphylococcus aureus biofilms than either alone. To test our hypothesis, S. aureus was grown in a flat plate flow cell reactor. Confocal laser scanning microscopy images were analyzed to quantify changes in biofilm structure. We used dissolved oxygen microelectrodes to quantify how vancomycin and maltodextrin affected the respiration rate and oxygen penetration into the biofilm. We found that treatment with vancomycin or maltodextrin altered biofilm structure. The effect on the structure was significant when they were used simultaneously to treat S. aureus biofilms. In addition, vancomycin treatment increased the oxygen respiration rate, while maltodextrin treatment caused an increase and then a decrease. An increased maltodextrin concentration decreased the diffusivity of the antibiotic. Overall, we conclude that (1) an increased maltodextrin concentration decreases vancomycin diffusion but increases the osmotic effect, leading to the optimum treatment condition, and (2) the combination of vancomycin and maltodextrin is more effective against S. aureus biofilms than either alone. Vancomycin and maltodextrin act together to increase the effectiveness of treatment against S. aureus biofilm growth.

Characterisation of the physical composition and microbial community structure of biofilms within a model full-scale drinking water distribution system

Within drinking water distribution systems (DWDS), microorganisms form multi-species biofilms on internal pipe surfaces. A matrix of extracellular polymeric substances (EPS) is produced by the attached community and provides structure and stability for the biofilm. If the EPS adhesive strength deteriorates or is overcome by external shear forces, biofilm is mobilised into the water potentially leading to degradation of water quality. However, little is known about the EPS within DWDS biofilms or how this is influenced by community composition or environmental parameters, because of the complications in obtaining biofilm samples and the difficulties in analysing EPS. Additionally, although biofilms may contain various microbial groups, research commonly focuses solely upon bacteria. This research applies an EPS analysis method based upon fluorescent confocal laser scanning microscopy (CLSM) in combination with digital image analysis (DIA), to concurrently characterize cells and EPS (carbohydrates and proteins) within drinking water biofilms from a full-scale DWDS experimental pipe loop facility with representative hydraulic conditions. Application of the EPS analysis method, alongside DNA fingerprinting of bacterial, archaeal and fungal communities, was demonstrated for biofilms sampled from different positions around the pipeline, after 28 days growth within the DWDS experimental facility. The volume of EPS was 4.9 times greater than that of the cells within biofilms, with carbohydrates present as the dominant component. Additionally, the greatest proportion of EPS was located above that of the cells. Fungi and archaea were established as important components of the biofilm community, although bacteria were more diverse. Moreover, biofilms from different positions were similar with respect to community structure and the quantity, composition and three-dimensional distribution of cells and EPS, indicating that active colonisation of the pipe wall is an important driver in material accumulation within the DWDS.

Investigation of microbial biofilm structure by laser scanning microscopy

Microbial bioaggregates and biofilms are hydrated three-dimensional structures of cells and extracellular polymeric substances (EPS). Microbial communities associated with interfaces and the samples thereof may come from natural, technical, and medical habitats. For imaging such complex microbial communities confocal laser scanning microscopy (CLSM) is the method of choice. CLSM allows flexible mounting and noninvasive three-dimensional sectioning of hydrated, living, as well as fixed samples. For this purpose a broad range of objective lenses is available having different working distance and resolution. By means of CLSM the signals detected may originate from reflection, autofluorescence, reporter genes/fluorescence proteins, fluorochromes binding to specific targets, or other probes conjugated with fluorochromes. Recorded datasets can be used not only for visualization but also for semiquantitative analysis. As a result CLSM represents a very useful tool for imaging of microbiological samples in combination with other analytical techniques.

Computational method for calculating fluorescence intensities within three-dimensional structures in cells

The use of fluorescence microscopy is central to cell biology in general, and essential to many fields (e.g., membrane traffic) that rely upon it to identify cellular locations of molecules under study and the extent to which they co-localize with others. Rigorous localization or co-localization data require quantitative image analyses that can vary widely between fields and laboratories. While most published data use two-dimensional images, there is an increasing appreciation for the advantages of collecting three-dimensional data sets. These include the ability to evaluate the entire cell and avoidance of focal plane bias. This is particularly important when imaging and quantifying changes in organelles with irregular borders and which vary in appearance between cells in a population, e.g., the Golgi. We describe a method developed for quantifying changes in signal intensity of one protein within any three-dimensional structure, defined by the presence of a different marker. We use as examples of this method the quantification of adaptor recruitment to transmembrane protein cargos at the Golgi though it can be directly applied to any site in the cell. Together, these advantages facilitate rigorous statistical testing of differences between conditions, despite variations in organelle structure, and we believe that this method of quantification of fluorescence data can be productively applied to a wide array of experimental questions.

Real time monitoring of biofilm development under flow conditions in porous media

Biofilm growth can impact the effectiveness of industrial processes that involve porous media. To better understand and characterize how biofilms develop and affect hydraulic properties in porous media, both spatial and temporal development of biofilms under flow conditions was investigated in a translucent porous medium by using Pseudomonas fluorescens HK44, a bacterial strain genetically engineered to luminesce in the presence of an induction agent. Real-time visualization of luminescent biofilm growth patterns under constant pressure conditions was captured using a CCD camera. Images obtained over 8 days revealed that variations in bioluminescence intensity could be correlated to biofilm cell density and hydraulic conductivity. These results were used to develop a real-time imaging method to study the dynamic behavior of biofilm evolution in a porous medium, thereby providing a new tool to investigate the impact of biological fouling in porous media under flow conditions.

Electrochemically active biofilms: facts and fiction. A review

This review examines the electrochemical techniques used to study extracellular electron transfer in the electrochemically active biofilms that are used in microbial fuel cells and other bioelectrochemical systems. Electrochemically active biofilms are defined as biofilms that exchange electrons with conductive surfaces: electrodes. Following the electrochemical conventions, and recognizing that electrodes can be considered reactants in these bioelectrochemical processes, biofilms that deliver electrons to the biofilm electrode are called anodic, ie electrode-reducing, biofilms, while biofilms that accept electrons from the biofilm electrode are called cathodic, ie electrode-oxidizing, biofilms. How to grow these electrochemically active biofilms in bioelectrochemical systems is discussed and also the critical choices made in the experimental setup that affect the experimental results. The reactor configurations used in bioelectrochemical systems research are also described and the authors demonstrate how to use selected voltammetric techniques to study extracellular electron transfer in bioelectrochemical systems. Finally, some critical concerns with the proposed electron transfer mechanisms in bioelectrochemical systems are addressed together with the prospects of bioelectrochemical systems as energy-converting and energy-harvesting devices.

Determining the effects of a spatially heterogeneous selection pressure on bacterial population structure at the sub-millimetre scale

A key interest of microbial ecology is to understand the role of environmental heterogeneity in shaping bacterial diversity and fitness. However, quantifying relevant selection pressures and their effects is challenging due to the number of parameters that must be considered and the multiple scales over which they act. In the current study, a model system was employed to investigate the effects of a spatially heterogeneous mercuric ion (Hg(2+)) selection pressure on a population comprising Hg-sensitive and Hg-resistant pseudomonads. The Hg-sensitive bacteria were Pseudomonas fluorescens SBW25::rfp and Hg-resistant bacteria were P. fluorescens SBW25 carrying a gfp-labelled, Hg resistance plasmid. In the absence of Hg, the plasmid confers a considerable fitness cost on the host, with µ(max) for plasmid-carrying cells relative to plasmid-free cells of only 0.66. Two image analysis techniques were developed to investigate the structure that developed in biofilms about foci of Hg (cellulose fibres imbued with HgCl(2)). Both techniques indicated selection for the resistant phenotype occurred only in small areas of approximately 178-353 μm (manually defined contour region analysis) or 275-350 μm (daime analysis) from foci. Hg also elicited toxic effects that reduced the growth of both Hg-sensitive and Hg-resistant bacteria up to 250 μm from foci. Selection for the Hg resistance phenotype was therefore highly localised when Hg was spatially heterogeneous. As such, for this model system, we define here the spatial scale over which selection operates. The ability to quantify changes in the strength of selection for particular phenotypes over sub-millimetre scales is useful for understanding the scale over which environmental variables affect bacterial populations.

Biofilm morphology as related to the porous media clogging

Aquifer recharge for the wastewater reuse has been considered and studied as a promising process to cope with the worldwide water scarcity. Soil clogging by an excessive growth of bacteria is often accompanied with the aquifer recharge. In this study, biofilm morphology and hydraulic conductivity were concurrently characterized at two flow rates and two levels of substrate concentrations. The experiments were conducted using a biofilm flow cell that was filled with glass beads. The biofilm images taken by confocal laser scanning microscopy (CLSM) were quantified by textural, areal, and fractal parameters. Hydraulic conductivity was monitored during the experiments. The flow velocity influenced the superficial morphology of biofilms and initial clogging time, while the substrate concentration affected biofilm density and clogging rate. Three different clogging mechanisms were suggested depending on the flow rate and substrate concentration: (1) clogging at a high flow rate can be accelerated by entrapped and accumulated biofilms, and can be easily eliminated by high shear force, (2) clogging at a low flow rate can be delayed for the time of local biofilm growths in the narrow pore necks, but the biofilm is rigid enough not to be sloughed, and (3) clogging in a solution with high substrate concentrations cannot be easily eliminated because of the growth of dense biofilms. The depicted biological clogging mechanisms will play a role in supporting studies about aquifer recharge.

Visualization of adherent micro-organisms using different techniques

The visualization and quantification of adherent bacteria is still one of the most relevant topics in microbiology. Besides electron microscopic techniques such as transmission electron microscopy, scanning electron microscopy and environmental scanning electron microscopy, modern fluorescence microscopic approaches based on fluorogenic dyes offer detailed insight into bacterial biofilms. The aim of the present review was to provide an overview of the advantages and disadvantages of different methods for visualization of adherent bacteria with a special focus on the experiences gained in dental research.

Image analysis software based on color segmentation for characterization of viability and physiological activity of biofilms

The novel image analysis software package bioImage_L was tested to calculate biofilm structural parameters in oral biofilms stained with dual-channel fluorescent markers. By identifying color tonalities in situ, the software independently processed the color subpopulations and characterized the viability and metabolic activity of biofilms.

Combined use of confocal laser scanning microscopy (CLSM) and Raman microscopy (RM): investigations on EPS-Matrix

Confocal laser scanning microscopy (CLSM) was applied in combination with Raman microscopy (RM) for the characterization of heterotrophic biofilms. Compared to CLSM, RM allows for a deeper insight into the chemical structure of extracellular polymeric substances (EPS) of the biofilm matrix. A low load of glucose (2 g m(-2)d(-1)) was applied as substrate to ensure small growth rates of the heterotrophic biofilm. To investigate the influence of hydrodynamic conditions on the chemical composition of EPS, a three funnel flow system was used, wherein biofilms were grown at Reynolds numbers of 1000, 2500 and 4000, respectively. 31 and 92 days after inoculation with activated sludge supernatant RM was applied as an additional technique to standard CLSM measurements for a more detailed analysis of the biofilm matrix. Polysaccharide-related Raman bands are in good agreement with the lectin binding analysis from CLSM. For the older biofilm, lectin binding analysis showed no change in the composition of EPS, whereas Raman spectra pointed out a change of EPS composition from predominantly polysaccharides to predominantly (glyco) proteins. For the applied substrate condition no significant influence of the Reynolds number on the chemical properties was observed.

Distribution of Nitrosomonas europaea and Nitrobacter winogradskyi in an autotrophic nitrifying biofilm reactor as depicted by molecular analyses and mathematical modelling

The autotrophic two-species biofilm from the packed bed reactor of a life-support system, containing Nitrosomonas europaea ATCC 19718 and Nitrobacter winogradskyi ATCC 25391, was analysed after 4.8 years of continuous operation performing complete nitrification. Real-time quantitative polymerase chain reaction (Q-PCR) was used to quantify N. europaea and N. winogradskyi along the vertical axis of the reactor, revealing a spatial segregation of N. europaea and N. winogradskyi. The main parameters influencing the spatial segregation of both nitrifiers along the bed were assessed through a multi-species one-dimensional biofilm model generated with AQUASIM software. The factor that contributed the most to this distribution profile was a small deviation from the flow pattern of a perfectly mixed tank towards plug-flow. The results indicate that the model can estimate the impact of specific biofilm parameters and predict the nitrification efficiency and population dynamics of a multispecies biofilm.

A two-step procedure for automatic and accurate segmentation of volumetric CLSM biofilm images

This paper presents a robust two-step segmentation procedure for the study of biofilm structure. Without user intervention, the procedure segments volumetric biofilm images generated by a confocal laser scanning microscopy (CLSM). This automated procedure implements an anisotropic diffusion filter as a preprocessing step and a 3D extension of the Otsu method for thresholding. Applying the anisotropic diffusion filter to even low-contrast CLSM images significantly improves the segmentation obtained with the 3D Otsu method. A comparison of the results for several CLSM data sets demonstrated that the accuracy of this procedure, unlike that of the objective threshold selection algorithm (OTS), is not affected by biofilm coverage levels and thus fills an important gap in developing a robust and objective segmenting procedure. The effectiveness of the present segmentation procedure is shown for CLSM images containing different bacterial strains. The image saturation handling capability of this procedure relaxes the constraints on user-selected gain and intensity settings of a CLSM. Therefore, this two-step procedure provides an automatic and accurate segmentation of biofilms that is independent of biofilm coverage levels and, in turn, lays a solid foundation for achieving objective analysis of biofilm structural parameters.

Toward automated analysis of biofilm architecture: bias caused by extraneous confocal laser scanning microscopy images

An increasing number of studies utilize confocal laser scanning microscopy (CLSM) for in situ visualization of biofilms and rely on the use of image analysis programs to extract quantitative descriptors of architecture. Recently, designed programs have begun incorporating procedures to automatically determine threshold values for three-dimensional CLSM image stacks. We have found that the automated threshold calculation is biased when a stack contains images lacking pixels of biological significance. Consequently, we have created the novel program Auto PHLIP-ML to resolve this bias by iteratively excluding extraneous images based on their area coverage of biomass. A procedure was developed to identify the optimal percent area coverage value used for extraneous image removal (PACVEIR). The optimal PACVEIR was defined to occur when the standard deviation of mean thickness, determined from replicate image stacks, was at a maximum, because it more accurately reflected inherent structural variation. Ten monoculture biofilms of either Ralstonia eutropha JMP228n::gfp or Acinetobacter sp. strain BD413 were tested to verify the routine. All biofilms exhibited an optimal PACVEIR between 0 and 1%. Prior to the exclusion of extraneous images, JMP228n::gfp appeared to develop more homogeneous biofilms than BD413. However, after the removal of extraneous images, JMP228n::gfp biofilms were found to form more heterogeneous biofilms. Similarly, JMP228n::gfp biofilms grown on glass surfaces vis-à-vis polyethylene membranes produced significantly different architectures after extraneous images had been removed but not when such images were included in threshold calculations. This study shows that the failure to remove extraneous images skewed a seemingly objective analysis of biofilm architecture and significantly altered statistically derived conclusions.

Quantification of uncultured microorganisms by fluorescence microscopy and digital image analysis

Traditional cultivation-based methods to quantify microbial abundance are not suitable for analyses of microbial communities in environmental or medical samples, which consist mainly of uncultured microorganisms. Recently, different cultivation-independent quantification approaches have been developed to overcome this problem. Some of these techniques use specific fluorescence markers, for example ribosomal ribonucleic acid targeted oligonucleotide probes, to label the respective target organisms. Subsequently, the detected cells are visualized by fluorescence microscopy and are quantified by direct visual cell counting or by digital image analysis. This article provides an overview of these methods and some of their applications with emphasis on (semi-)automated image analysis solutions.

daime, a novel image analysis program for microbial ecology and biofilm research

Combinations of microscopy and molecular techniques to detect, identify and characterize microorganisms in environmental and medical samples are widely used in microbial ecology and biofilm research. The scope of these methods, which include fluorescence in situ hybridization (FISH) with rRNA-targeted probes, is extended by digital image analysis routines that extract from micrographs important quantitative data. Here we introduce daime (digital image analysis in microbial ecology), a new computer program integrating 2-D and 3-D image analysis and visualization functionality, which has previously not been available in a single open-source software package. For example, daime automatically finds 2-D and 3-D objects in images and confocal image stacks, and offers special functions for quantifying microbial populations and evaluating new FISH probes. A novel feature is the quantification of spatial localization patterns of microorganisms in complex samples like biofilms. In combination with '3D-FISH', which preserves the 3-D structure of samples, this stereological technique was applied in a proof of principle experiment on activated sludge and provided quantitative evidence that functionally linked ammonia and nitrite oxidizers cluster together in their habitat. This image analysis method complements recent molecular techniques for analysing structure-function relationships in microbial communities and will help to characterize symbiotic interactions among microorganisms.

Analysis of a marine phototrophic biofilm by confocal laser scanning microscopy using the new image quantification software PHLIP

Background

Confocal laser scanning microscopy (CLSM) is the method of choice to study interfacial biofilms and acquires time-resolved three-dimensional data of the biofilm structure. CLSM can be used in a multi-channel modus where the different channels map individual biofilm components. This communication presents a novel image quantification tool, PHLIP, for the quantitative analysis of large amounts of multichannel CLSM data in an automated way. PHLIP can be freely downloaded from

Results

PHLIP is an open source public license Matlab toolbox that includes functions for CLSM imaging data handling and ten image analysis operations describing various aspects of biofilm morphology. The use of PHLIP is here demonstrated by a study of the development of a natural marine phototrophic biofilm. It is shown how the examination of the individual biofilm components using the multi-channel capability of PHLIP allowed the description of the dynamic spatial and temporal separation of diatoms, bacteria and organic and inorganic matter during the shift from a bacteria-dominated to a diatom-dominated phototrophic biofilm. Reflection images and weight measurements complementing the PHLIP analyses suggest that a large part of the biofilm mass consisted of inorganic mineral material.

Conclusion

The presented case study reveals new insight into the temporal development of a phototrophic biofilm where multi-channel imaging allowed to parallel monitor the dynamics of the individual biofilm components over time. This application of PHLIP presents the power of biofilm image analysis by multi-channel CLSM software and demonstrates the importance of PHLIP for the scientific community as a flexible and extendable image analysis platform for automated image processing.

Refining competition in the self-organising tree map for unsupervised biofilm image segmentation

The Self Organising Tree Map (SOTM) neural network is investigated as a means of segmenting micro-organisms from confocal microscope image data. Features describing pixel and regional intensities, phase congruency and spatial proximity are explored in terms of their impact on the segmentation of bacteria and other micro-organisms. The significance of individual features is investigated, and it is proposed that, within the context of micro-biological image segmentation, better object delineation can be achieved if certain features are more dominant in the initial stages of learning. In this way, other features are allowed to become more/less significant as learning progresses: as more knowledge is acquired about the data being segmented. We argue that the efficiency and flexibility of the SOTM in adapting to, and preserving the topology of input space, makes it an appropriate candidate for implementing this idea. We propose a refinement to the competitive search strategy that allows for a more appropriate fusion of signal and proximal features, thereby promoting a segmentation that is more sensitive to the regional associations of different microbial matter. A refined stop criterion is also suggested such that the dynamically generated number of classes becomes more data dependant. Preliminary experiments are presented and it is found that favouring intensity characteristics in the early phases of learning, whilst relaxing proximity constraints in later phases of learning, offers a general mechanism through which we can improve the segmentation of microbial constituents.

Three-dimensional biofilm structure quantification

Quantitative parameters describing biofilm physical structure have been extracted from three-dimensional confocal laser scanning microscopy images and used to compare biofilm structures, monitor biofilm development, and quantify environmental factors affecting biofilm structure. Researchers have previously used biovolume, volume to surface ratio, roughness coefficient, and mean and maximum thicknesses to compare biofilm structures. The selection of these parameters is dependent on the availability of software to perform calculations. We believe it is necessary to develop more comprehensive parameters to describe heterogeneous biofilm morphology in three dimensions. This research presents parameters describing three-dimensional biofilm heterogeneity, size, and morphology of biomass calculated from confocal laser scanning microscopy images. This study extends previous work which extracted quantitative parameters regarding morphological features from two-dimensional biofilm images to three-dimensional biofilm images. We describe two types of parameters: (1) textural parameters showing microscale heterogeneity of biofilms and (2) volumetric parameters describing size and morphology of biomass. The three-dimensional features presented are average (ADD) and maximum diffusion distances (MDD), fractal dimension, average run lengths (in X, Y and Z directions), aspect ratio, textural entropy, energy and homogeneity. We discuss the meaning of each parameter and present the calculations in detail. The developed algorithms, including automatic thresholding, are implemented in software as MATLAB programs which will be available at site prior to publication of the paper.

Bilevel thresholding of floc images

Frequently encountered problems on bilevel thresholding of floc images include information loss during the image conversion stage, sampling bias owing to spatially inhomogeneous luminous flux over an optical microscope image or among a series of images, thresholding error adopting various algorithms, and resampling errors during three-dimensional reconstruction. Among these steps the choice of thresholding algorithm could yield most of the processing error. Ways to reduce the potential processing errors are discussed.

Bilevel thresholding of sliced image of sludge floc

This work examined the feasibility of employing various thresholding algorithms to determining the optimal bilevel thresholding value for estimating the geometric parameters of sludge flocs from the microtome sliced images and from the confocal laser scanning microscope images. Morphological information extracted from images depends on the bilevel thresholding value. According to the evaluation on the luminescence-inverted images and fractal curves (quadric Koch curve and Sierpinski carpet), Otsu's method yields more stable performance than other histogram-based algorithms and is chosen to obtain the porosity. The maximum convex perimeter method, however, can probe the shapes and spatial distribution of the pores among the biomass granules in real sludge flocs. A combined algorithm is recommended for probing the sludge floc structure.

Quantifying biofilm structure: facts and fiction

There is no doubt among biofilm researchers that biofilm structure is important to many biofilm processes, such as the transport of nutrients to deeper layers of the biofilm. However, biofilm structure is an elusive term understood only qualitatively, and as such it cannot be directly correlated with any measurable parameters characterizing biofilm performance. To correlate biofilm structure with the parameters characterizing biofilm performance, such as the rate of nutrient transport within the space occupied by the biofilms, biofilm structure must first be quantified and expressed numerically on an appropriate scale. The task of extracting numerical parameters quantifying biofilm structure relies on using biofilm imaging and image analysis. Although defining parameters characterizing biofilm structure is relatively straightforward, and multiple parameters have been described in the computer science literature, interpreting the results of such analyses is not trivial. Existing computer software developed by several research groups, including ours, for the sole purpose of analyzing biofilm images helps quantify parameters from biofilm images but does nothing to help interpret the results of such analyses. Although computing structural parameters from biofilm images permits correlating biofilm structure with other biofilm processes, the meaning of the results is not obvious. The first step to understanding the quantification of biofilm structure, developing image analysis, methods to quantify information from biofilm images, has been made by several research groups. The next step is to explain the meaning of these analyses. This presentation explains the meaning of several parameters commonly used to characterize biofilm structure. It also reviews the authors' research and experience in quantifying biofilm structure and their attempts to quantitatively relate biofilm structure to fundamental biofilm processes.

Measuring the thickness of an outer layer of viable bacteria in an oral biofilm by viability mapping

Bacterial biofilms have been reported to contain distinct regions of viable and nonviable bacteria. The purpose of this study was to identify such regions in biofilms of oral bacteria and to determine their dimensions. Oral biofilms were grown aerobically in a constant-depth film fermenter (CDFF) and studied using confocal laser scanning microscopy (CLSM) incorporating viability staining with water immersion lenses. A variety of viability distributions were observed, including biofilm "stacks" possessing an outer layer of viable bacteria surrounding an internal core of nonviable bacteria. Using image analysis tools, we measured the thickness of this outer viable region, in the x-y plane, from single confocal optical sections, and determined the mean angle (theta) of these portions of the biofilm stack (10.93 degrees ). x-y plane thickness data in conjunction with the data on the angle of the stack returned the thickness of the outer viable layer perpendicular to the bulk medium flow as 36.62 microm (31.61-42.21 microm accounting for 95% confidence for variation in both the x-y plane thickness and theta). We have shown that CLSM, in conjunction with vital stains and image analysis techniques, can reveal viability patterns in biofilms and where appropriate can be used to measure the dimensions of these structures.

Assessing technician effects when extracting quantities from microscope images

Consider an experiment where the response is based on an image; e.g., an image captured to a computer file by a digital camera mounted on a microscope. Suppose relevant quantitative measures are extracted from the images so that results can be analyzed by conventional statistical methods. The steps involved in extracting the measures may require that the technicians, who are processing the images, perform some subjective manipulations. In this case, it is important to determine the bias and variability, if any, attributable to the technicians' decisions. This paper describes the experimental design and statistical analyses that are useful for those determinations. The design and analysis are illustrated by application to two biofilm research projects that involved quantitative image analysis. In one investigation, the technician was required to choose a threshold level, then the image analysis program automatically extracted relevant measures from the resulting black and white image. In the other investigation, the technician was required to choose fiducial points in each of two images collected on different microscopes; then the image analysis program registered the images by stretching, rotating, and overlaying them, so that their quantitative features could be correlated. These investigations elucidated the effects of the technicians' decisions, thereby helping us to assess properly the statistical uncertainties in the conclusions for the primary experiments.

Influence of hydrodynamics and cell signaling on the structure and behavior of Pseudomonas aeruginosa biofilms

Biofilms were grown from wild-type (WT) Pseudomonas aeruginosa PAO1 and the cell signaling lasI mutant PAO1-JP1 under laminar and turbulent flows to investigate the relative contributions of hydrodynamics and cell signaling for biofilm formation. Various biofilm morphological parameters were quantified using Image Structure Analyzer software. Multivariate analysis demonstrated that both cell signaling and hydrodynamics significantly (P < 0.000) influenced biofilm structure. In turbulent flow, both biofilms formed streamlined patches, which in some cases developed ripple-like wave structures which flowed downstream along the surface of the flow cell. In laminar flow, both biofilms formed monolayers interspersed with small circular microcolonies. Ripple-like structures also formed in four out of six WT biofilms, although their velocity was approximately 10 times less than that of those that formed in the turbulent flow cells. The movement of biofilm cell clusters over solid surfaces may have important clinical implications for the dissemination of biofilm subject to fluid shear, such as that found in catheters. The ability of the cell signaling mutant to form biofilms in high shear flow demonstrates that signaling mechanisms are not required for the formation of strongly adhered biofilms. Similarity between biofilm morphologies in WT and mutant biofilms suggests that the dilution of signal molecules by mass transfer effects in faster flowing systems mollifies the dramatic influence of signal molecules on biofilm structure reported in previous studies.

Growing reproducible biofilms with respect to structure and viable cell counts

We have developed a new method of growing 4-day-old biofilms that are reproducible, with respect to viable cell number and biofilm structure. To demonstrate the utility of the method, we grew biofilms composed of Pseudomonas aeruginosa (ATCC#700829), P. fluorescens (ATCC#700830) and Klebsiella pneumoniae (ATCC#700831), 18 times in flat-plate reactors under well-defined conditions of: flow rate, nutrient concentration, temperature, inoculum and growth rate. The resulting 4-day-old biofilms were approximately 200-300 microm thick and exhibited a high degree of reproducibility. The number of viable cells that accumulated per unit surface area and the biofilm areal porosity were reproduced within 10% error. We have also quantified other parameters characterizing biofilm structure using biofilm-imaging techniques: fractal dimension, textural entropy and diffusion distance as auxiliary parameters characterizing the reproducibility of biofilm accumulation. As a result of analysis, we have introduced a new parameter to better quantify and characterize the number of viable cells in biofilms, "specific number of viable cells" (SNVC). This parameter is the viable cell number normalized with respect to the surface area covered by the biofilm and with respect to the biomass of the biofilm. This new descriptor represents the dynamics of biofilm accumulation better than the traditionally used colony-forming unit (CFU) per surface area covered by the biofilm because it accounts not only for the surface coverage but also for the biofilm thickness.